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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 1
Atmos. Meas. Tech., 8, 281-299, 2015
https://doi.org/10.5194/amt-8-281-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 8, 281-299, 2015
https://doi.org/10.5194/amt-8-281-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 14 Jan 2015

Research article | 14 Jan 2015

Use of neural networks in ground-based aerosol retrievals from multi-angle spectropolarimetric observations

A. Di Noia et al.
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Manuscript under review for AMT
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Cited articles  
Aires, F., Rossow, W. B., Scott, N. A., and Chédin, A.: Remote sensing from the infrared atmospheric sounding interferometer instrument 1. Compression, denoising, and first-guess retrieval algorithms, J. Geophys. Res., 107, 4619, https://doi.org/10.1029/2001JD000955, 2002.
Alexander, D.: Volcanic ash in the atmosphere and risks for civil aviation: A study in European crisis management, Int. J. Disaster Risk Sci., 4, 9–19, https://doi.org/10.1007/s13753-013-0003-0, 2013.
Anderson, J. O., Thundiyil, J. G., and Stolbach, A.: Clearing the air: A review of the effects of particulate matter air pollution on human health, J. Med. Toxicol., 8, 166–175, https://doi.org/10.1007/s13181-011-0203-1, 2012.
Antonelli, P., Revercomb, H. E., Sromovsky, L. A., Smith, W. L., Knuteson, R. O., Tobin, D. C., Garcia, R. K., Howell, H. B., Huang, H.-L., and Best, F. A.: A principal component noise filter for high spectral resolution infrared measurements, J. Geophys. Res., 109, D23102, https://doi.org/10.1029/2004JD004862, 2004.
Bishop, C. M.: Neural Networks for Pattern Recognition, Oxford University Press, New York, NY, USA, 1995a.
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A neural network algorithm has been developed to retrieve aerosol microphysical parameters from ground-based measurements of skylight intensity and polarization. The neural network is capable of producing accurate estimates of aerosol optical thicknesses, effective radii and refractive index. In addition, it is shown that the use of the neural retrievals as initial guess for an iterative retrieval algorithm results in improved convergence and retrieval accuracy.
A neural network algorithm has been developed to retrieve aerosol microphysical parameters from...
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